A normal section plane method for profile error analysis of five-axis machine tools based on the ideal tool flank milling surface

The existing studies on profile error analysis and machining accuracy measurement do not consider the impact of the theoretical errors on the machine tool accuracy measurement. Therefore, this study proposes an estimation method of the surface profile error based on the normal section plane, using the theoretical flank milled surface for comparison. This effectively improves the accuracy of profile error estimation. The theoretical flank milled surface is the surface machined by flank milling under ideal conditions. Hence, compared to the traditional analysis method based on the designed three-dimensional model of S-shaped test pieces, the calculated profile error of this method does not include theoretical errors, thereby eliminating the impact of theoretical errors on machine tool accuracy measurement and evaluation. First, an improved method for continuous parameterized dual spline interpolation was proposed. It simplifies the solution of the singular problem of the coefficient matrix of the spline basis function and obtains a continuous ideal machining tool axis trajectory surface with complete geometric characteristics. Next, a method for constructing the theoretical flank milled surface machined with a cylindrical milling tool using equidistant mapping characteristics was proposed; then, the differential transformation relationship at the cutting contact point of the curved surface under the influence of tool path errors was established. Furthermore, the normal section plane method based on the differentiation of the cutting contact point was proposed. The problem of solving the distance from a point to a surface is converted to the problem of solving the distance from a point to a curve in the normal section plane. This improves the accuracy of profile error estimation. The effectiveness of the method was verified by comparing the analysis results of the profile errors of a typical cylindrical surface with the point to surface and the point to curve methods.

A NOVEL DESIGN CONCEPT FOR A THERMALLY STABLE LINEAR SCALE USING TWO DIFFERENT MATERIALS

Linear scale has significant impacts on the machine tool accuracy, since the positioning of the linear axes are controlled by its measurement. This paper presents a novel concept of linear scale design which can provide high thermal stability with low cost. This concept applies two different materials: a steel linear scale attached mechanically on a carbon fiber reinforced plastic (CFRP) tube. Attaching this two materials, the thermal behavior of the steel scale can be mechanically compensated by the CFRP tube when the temperature changes. The potential of the design concept is analyzed based on the experiment results.

Special Issue on Machine Accuracy Evaluation

The accuracy of a three-dimensional (3D) positioning system can ultimately be evaluated via measurement of a 3D vector between command and actual end-effector positions at arbitrary points over the entire workspace. This is a simple, yet challenging, metrological problem. The motion accuracy of a machine tool is traditionally evaluated on an axis-to-axis basis, with every error motion of every axis being independently measured as part of a one-dimensional measurement process in a different setup. Toward the ultimate goal of 3D position measurement over the entire workspace, research efforts have offered several new, practical measurement technologies. This special issue covers the technical and academic efforts regarding the evaluation of machine tool accuracy. The papers in this special issue clarify the latest research frontiers regarding machine tool accuracy from a metrological viewpoint. In the first paper, by Montavon et al., error calibration technologies and their management are reviewed within the Internet of production concept. Long-term accuracy monitoring and management are clearly among the most crucial technical challenges faced regarding machine tools, and the work by Xing et al. is related to them. Ibaraki et al. presented machining tests to evaluate the thermal distortion of a machine tool. Peukert et al. studied the dynamic interaction between machine tools and their foundations. Various 3D measurement schemes for determining machine error motions have been investigated by many researchers, and some have been implemented in industrial applications. Kenno et al. and Florussen et al. investigated 3D measurement using the R-test for five-axis machines. Miller et al. studied simultaneous measurement of six-degree-of-freedom error motions of a linear axis. Nagao et al. presented an error calibration method for a parallel kinematic machine tool. The editors appreciate the contributions of all the authors, as well as the work of the reviewers. We are confident that this special issue will further encourage research and engineering work for improving the accuracy and performance of machine tools.

Effect of Supply Cooling Oil Temperature in Structural Cooling Channels on the Positioning Accuracy of Machine Tools

ABSTRACTIn this study, the thermal deformation of a machine tool structure due to the heat generated during operation was analyzed, and embedded cooling channels were applied to exchange the heat generated during the operation to achieve thermal error suppression. Then, the finite volume method was used to simulate the effect of cooling oil temperature on thermal deformation, and the effect of thermal suppression was experimentally studied using a feed system combined with a cooler to improve the positioning accuracy of the machine tool. In this study, the supply oil temperature in the structural cooling channels was found to significantly affect the position accuracy of the moving table and moving carrier. If the supply oil temperature in the cooling channels is consistent with the operational ambient temperature, the position accuracy of the moving table in the Y direction and the moving carrier in the X and Z directions has the best performance under different feed rates. From the thermal suppression experiments of the embedded cooling channels, the positioning accuracy of the feed system can be improved by approximately 25.5 % during the dynamic feeding process. Furthermore, when the hydrostatic guideway is cooled and dynamic feeding is conducted, positioning accuracy can be improved by up to 47.8 %. The machining accuracy can be improved by approximately 60 % on average by using the embedded cooling channels in this study. Therefore, thermal suppression by the cooling channels in this study can not only effectively improve the positioning accuracy but also enhance machining accuracy, proving that the method is effective for enhancing machine tool accuracy.

Machine Tool Volumetric Error Features Extraction and Classification Using Principal Component Analysis and K-Means

Volumetric errors (VE) are related to the machine tool accuracy state. Extracting features from the complex VE data provides with a means to characterize this data. VE feature classification can reveal the machine tool accuracy states. This paper presents a study on how to use principal component analysis (PCA) to extract the features of VE and how to use the K-means method for machine tool accuracy state classification. The proposed data processing methods have been tested with the VE data acquired from a five-axis machine tool with different states of malfunction. The results indicate that the PCA and K-means are capable of extracting the VE feature information and classifying the fault states including the C axis encoder fault, uncalibrated C axis encoder fault, and pallet location fault from the machine tool normal states. This research provides a new way for VE features extraction and classification.

Adaptive decision support for suggesting a machine tool maintenance strategy

Purpose The purpose of this paper is to produce a decision support aid for machine tool owners to utilise while deciding upon a maintenance strategy. Furthermore, the decision support tool is adaptive and capable of suggesting different strategies by monitoring for any change in machine tool manufacturing accuracy. Design/methodology/approach A maintenance cost estimation model is utilised within the research and development of this decision support system (DSS). An empirical-based methodology is pursued and validated through case study analysis. Findings A case study is provided where a schedule of preventative maintenance actions is produced to reduce the need for the future occurrences of reactive maintenance actions based on historical machine tool accuracy information. In the case study, a 28 per cent reduction in predicted accuracy-related expenditure is presented, equating to a saving of £14k per machine over a five year period. Research limitations/implications The emphasis on improving machine tool accuracy and reducing production costs is increasing. The presented research is pioneering in the development of a software-based tool to help reduce the requirement on domain-specific expert knowledge. Originality/value The paper presents an adaptive DSS to assist with maintenance strategy selection. This is the first of its kind and is able to suggest a preventative strategy for those undertaking only reactive maintenance. This is of value for both manufacturers and researchers alike. Manufacturers will benefit from reducing maintenance costs, and researchers will benefit from the development and application of a novel decision support technique.